14 resultados para SCGE (Spatial Computable General Equilibrium) model

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The present work, then, is concerned with the forgotten elements of the Lebanese economy, agriculture and rural development. It investigates the main problematic which arose from these forgotten components, in particular the structure of the agricultural sector, production technology, income distribution, poverty, food security, territorial development and local livelihood strategies. It will do so using quantitative Computable General Equilibrium (CGE) modeling and a qualitative phenomenological case study analysis, both embedded in a critical review of the historical development of the political economy of Lebanon, and a structural analysis of its economy. The research shows that under-development in Lebanese rural areas is not due to lack of resources, but rather is the consequence of political choices. It further suggests that agriculture – in both its mainstream conventional and its innovative locally initiated forms of production – still represents important potential for inducing economic growth and development. In order to do so, Lebanon has to take full advantage of its human and territorial capital, by developing a rural development strategy based on two parallel sets of actions: one directed toward the support of local rural development initiatives, and the other directed toward intensive form of production. In addition to its economic returns, such a strategy would promote social and political stability.

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In this thesis, the field of study related to the stability analysis of fluid saturated porous media is investigated. In particular the contribution of the viscous heating to the onset of convective instability in the flow through ducts is analysed. In order to evaluate the contribution of the viscous dissipation, different geometries, different models describing the balance equations and different boundary conditions are used. Moreover, the local thermal non-equilibrium model is used to study the evolution of the temperature differences between the fluid and the solid matrix in a thermal boundary layer problem. On studying the onset of instability, different techniques for eigenvalue problems has been used. Analytical solutions, asymptotic analyses and numerical solutions by means of original and commercial codes are carried out.

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Nell’ambito del progetto multidisciplinare “Coastal Salt Water Intrusion”, che si propone di indagare “l’Intrusione salina nella costa ravennate con i conseguenti impatti territoriali-ambientali, connessi al previsto innalzamento del livello marino per cause climatiche e di subsidenza”, si inserisce il presente studio con l’obiettivo di fornire una caratterizzazione idrogeochimica delle acque di falda e superficiali e un modello geochimico generale sui processi di salinizzazione o desalinizzazione in atto nella falda freatica costiera della costa ravennate. E’ stato fatto un confronto fra tre metodiche di estrazione del complesso di scambio della matrice solida dell’acquifero che utilizzano rispettivamente acetato di ammonio, cloruro di bario e argento-tiourea. Sono stati posizionati 5 transetti perpendicolari alla linea di costa per un totale di 44 punti di campionamento con due campagne di prelievi, al termine della primavera e al termine dell’estate. La caratterizzazione dei processi di mixing e scambio ionico con la matrice solida dell’acquifero è avvenuta mediante analisi dei cationi ed anioni fondamentali, determinazione della CEC sulla matrice solida dell’acquifero, modellizzazione mixing/scambio ionico, modellizzazione della composizione teorica della frazione scambiabile in funzione della composizione acqua all’equilibrio e interpolazione geostatistica dei dati raccolti e costruzione di mappe geochimiche (curve di iso-concentrazione). La metodologia di estrazione che utilizza il bario-cloruro è risultata la più affidabile. Le acque prelevate dalla falda superficiale evidenziano miscelazione in varie proporzioni acqua marina/acqua dolce, scambi ionici per interazione acqua/sedimento, dissoluzione di CaSO4.2H2O. I processi di salinizzazione e/o addolcimento mostrano una significativa variabilità nello spazio (variabilità legata alla distanza dalla costa, al profilo topografico e alla distribuzione dei corpi sabbiosi litoranei) e nel tempo (variabilità legata alla piovosità e alla gestione delle acque superficiali e del sottosuolo). La complessa variabilità spazio-temporale dei processi in atto nella falda superficiale non consente di evidenziare una complessiva prevalenza di fenomeni di salinizzazione rispetto a quelli di addolcimento.

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The advances that have been characterizing spatial econometrics in recent years are mostly theoretical and have not found an extensive empirical application yet. In this work we aim at supplying a review of the main tools of spatial econometrics and to show an empirical application for one of the most recently introduced estimators. Despite the numerous alternatives that the econometric theory provides for the treatment of spatial (and spatiotemporal) data, empirical analyses are still limited by the lack of availability of the correspondent routines in statistical and econometric software. Spatiotemporal modeling represents one of the most recent developments in spatial econometric theory and the finite sample properties of the estimators that have been proposed are currently being tested in the literature. We provide a comparison between some estimators (a quasi-maximum likelihood, QML, estimator and some GMM-type estimators) for a fixed effects dynamic panel data model under certain conditions, by means of a Monte Carlo simulation analysis. We focus on different settings, which are characterized either by fully stable or quasi-unit root series. We also investigate the extent of the bias that is caused by a non-spatial estimation of a model when the data are characterized by different degrees of spatial dependence. Finally, we provide an empirical application of a QML estimator for a time-space dynamic model which includes a temporal, a spatial and a spatiotemporal lag of the dependent variable. This is done by choosing a relevant and prolific field of analysis, in which spatial econometrics has only found limited space so far, in order to explore the value-added of considering the spatial dimension of the data. In particular, we study the determinants of cropland value in Midwestern U.S.A. in the years 1971-2009, by taking the present value model (PVM) as the theoretical framework of analysis.

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The dissertation consists of four papers that aim at providing new contributions in the field of macroeconomics, monetary policy and financial stability. The first paper proposes a new Dynamic Stochastic General Equilibrium (DSGE) model with credit frictions and a banking sector to study the pro-cyclicality of credit and the role of different prudential regulatory frameworks in affecting business cycle fluctuations and in restoring macroeconomic and financial stability. The second paper develops a simple DSGE model capable of evaluating the effects of large purchases of treasuries by central banks. This theoretical framework is employed to evaluate the impact on yields and the macroeconomy of large purchases of medium- and long-term government bonds recently implemented in the US and UK. The third paper studies the effects of ECB communications about unconventional monetary policy operations on the perceived sovereign risk of Italy over the last five years. The empirical results are derived from both an event-study analysis and a GARCH model, which uses Italian long-term bond futures to disentangle expected from unexpected policy actions. The fourth paper proposes a DSGE model with an endogenous term structure of interest rates, which is able to replicate the stylized facts regarding the yield curve and the term premium in the US over the period 1987:3-2011:3, without compromising its ability to match macro dynamics.

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Small-scale dynamic stochastic general equilibrium have been treated as the benchmark of much of the monetary policy literature, given their ability to explain the impact of monetary policy on output, inflation and financial markets. One cause of the empirical failure of New Keynesian models is partially due to the Rational Expectations (RE) paradigm, which entails a tight structure on the dynamics of the system. Under this hypothesis, the agents are assumed to know the data genereting process. In this paper, we propose the econometric analysis of New Keynesian DSGE models under an alternative expectations generating paradigm, which can be regarded as an intermediate position between rational expectations and learning, nameley an adapted version of the "Quasi-Rational" Expectatations (QRE) hypothesis. Given the agents' statistical model, we build a pseudo-structural form from the baseline system of Euler equations, imposing that the length of the reduced form is the same as in the `best' statistical model.

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Gossip protocols have proved to be a viable solution to set-up and manage largescale P2P services or applications in a fully decentralised scenario. The gossip or epidemic communication scheme is heavily based on stochastic behaviors and it is the fundamental idea behind many large-scale P2P protocols. It provides many remarkable features, such as scalability, robustness to failures, emergent load balancing capabilities, fast spreading, and redundancy of information. In some sense, these services or protocols mimic natural system behaviors in order to achieve their goals. The key idea of this work is that the remarkable properties of gossip hold when all the participants follow the rules dictated by the actual protocols. If one or more malicious nodes join the network and start cheating according to some strategy, the result can be catastrophic. In order to study how serious the threat posed by malicious nodes can be and what can be done to prevent attackers from cheating, we focused on a general attack model aimed to defeat a key service in gossip overlay networks (the Peer Sampling Service [JGKvS04]). We also focused on the problem of protecting against forged information exchanged in gossip services. We propose a solution technique for each problem; both techniques are general enough to be applied to distinct service implementations. As gossip protocols, our solutions are based on stochastic behavior and are fully decentralized. In addition, each technique’s behaviour is abstracted by a general primitive function extending the basic gossip scheme; this approach allows the adoptions of our solutions with minimal changes in different scenarios. We provide an extensive experimental evaluation to support the effectiveness of our techniques. Basically, these techniques aim to be building blocks or P2P architecture guidelines in building more resilient and more secure P2P services.

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Introduction: Nocturnal frontal lobe epilepsy (NFLE) is a distinct syndrome of partial epilepsy whose clinical features comprise a spectrum of paroxysmal motor manifestations of variable duration and complexity, arising from sleep. Cardiovascular changes during NFLE seizures have previously been observed, however the extent of these modifications and their relationship with seizure onset has not been analyzed in detail. Objective: Aim of present study is to evaluate NFLE seizure related changes in heart rate (HR) and in sympathetic/parasympathetic balance through wavelet analysis of HR variability (HRV). Methods: We evaluated the whole night digitally recorded video-polysomnography (VPSG) of 9 patients diagnosed with NFLE with no history of cardiac disorders and normal cardiac examinations. Events with features of NFLE seizures were selected independently by three examiners and included in the study only if a consensus was reached. Heart rate was evaluated by measuring the interval between two consecutive R-waves of QRS complexes (RRi). RRi series were digitally calculated for a period of 20 minutes, including the seizures and resampled at 10 Hz using cubic spline interpolation. A multiresolution analysis was performed (Daubechies-16 form), and the squared level specific amplitude coefficients were summed across appropriate decomposition levels in order to compute total band powers in bands of interest (LF: 0.039062 - 0.156248, HF: 0.156248 - 0.624992). A general linear model was then applied to estimate changes in RRi, LF and HF powers during three different period (Basal) (30 sec, at least 30 sec before seizure onset, during which no movements occurred and autonomic conditions resulted stationary); pre-seizure period (preSP) (10 sec preceding seizure onset) and seizure period (SP) corresponding to the clinical manifestations. For one of the patients (patient 9) three seizures associated with ictal asystole were recorded, hence he was treated separately. Results: Group analysis performed on 8 patients (41 seizures) showed that RRi remained unchanged during the preSP, while a significant tachycardia was observed in the SP. A significant increase in the LF component was instead observed during both the preSP and the SP (p<0.001) while HF component decreased only in the SP (p<0.001). For patient 9 during the preSP and in the first part of SP a significant tachycardia was observed associated with an increased sympathetic activity (increased LF absolute values and LF%). In the second part of the SP a progressive decrease in HR that gradually exceeded basal values occurred before IA. Bradycardia was associated with an increase in parasympathetic activity (increased HF absolute values and HF%) contrasted by a further increase in LF until the occurrence of IA. Conclusions: These data suggest that changes in autonomic balance toward a sympathetic prevalence always preceded clinical seizure onset in NFLE, even when HR changes were not yet evident, confirming that wavelet analysis is a sensitive technique to detect sudden variations of autonomic balance occurring during transient phenomena. Finally we demonstrated that epileptic asystole is associated with a parasympathetic hypertonus counteracted by a marked sympathetic activation.

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The study of the impact of climate change on the environment has been based, until very recently, on an global approach, whose interest from a local point of view is very limited. This thesis, on the contrary, has treated the study of the impact of climate change in the Adriatic Sea basin following a twofold strategy of regionalization and integration of numerical models in order to reproduce the present and future scenarios of the system through a more and more realistic and solid approach. In particular the focus of the study was on the impact on the physical environment and on the sediment transport in the basin. This latter is a very new and original issue, to our knowledge still uninvestigated. The study case of the coastal area of Montenegro was particularly studied, since it is characterized by an important supply of sediment through the Buna/Bojana river, second most important in the Adriatic basin in terms of flow. To do this, a methodology to introduce the tidal processes in a baroclinic primitive equations Ocean General Circulation Model was applied and tidal processes were successfully reproduced in the Adriatic Sea, analyzing also the impacts they have on the mean general circulation, on salt and heat transport and on mixing and stratification of the water column in the different seasons of the year. The new hydrodynamical model has been further coupled with a wave model and with a river and sea sediment transport model, showing good results in the reproduction of sediment transport processes. Finally this complex coupled platform was integrated in the period 2001-2030 under the A1B scenario of IPCC, and the impact of climate change on the physical system and on sediment transport was preliminarily evaluated.

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Basic concepts and definitions relative to Lagrangian Particle Dispersion Models (LPDMs)for the description of turbulent dispersion are introduced. The study focusses on LPDMs that use as input, for the large scale motion, fields produced by Eulerian models, with the small scale motions described by Lagrangian Stochastic Models (LSMs). The data of two different dynamical model have been used: a Large Eddy Simulation (LES) and a General Circulation Model (GCM). After reviewing the small scale closure adopted by the Eulerian model, the development and implementation of appropriate LSMs is outlined. The basic requirement of every LPDM used in this work is its fullfillment of the Well Mixed Condition (WMC). For the dispersion description in the GCM domain, a stochastic model of Markov order 0, consistent with the eddy-viscosity closure of the dynamical model, is implemented. A LSM of Markov order 1, more suitable for shorter timescales, has been implemented for the description of the unresolved motion of the LES fields. Different assumptions on the small scale correlation time are made. Tests of the LSM on GCM fields suggest that the use of an interpolation algorithm able to maintain an analytical consistency between the diffusion coefficient and its derivative is mandatory if the model has to satisfy the WMC. Also a dynamical time step selection scheme based on the diffusion coefficient shape is introduced, and the criteria for the integration step selection are discussed. Absolute and relative dispersion experiments are made with various unresolved motion settings for the LSM on LES data, and the results are compared with laboratory data. The study shows that the unresolved turbulence parameterization has a negligible influence on the absolute dispersion, while it affects the contribution of the relative dispersion and meandering to absolute dispersion, as well as the Lagrangian correlation.

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L’Inserimento Eterofamigliare Supportato di Adulti (IESA) sofferenti di disturbi psichici consiste nell’accogliere persone in cura presso i servizi psichiatrici territoriali, nel proprio domicilio, integrandole nelle proprie relazioni famigliari. Obiettivo è migliorare la qualità di vita dell’utente e favorirne l’integrazione nella comunità. Obiettivo. Valutare gli esiti dello IESA, con un disegno di ricerca longitudinale, considerando: psicopatologia, benessere psicologico, funzionamento sociale e familiare. Metodologia. 40 soggetti: 20 pazienti e 20 ospitanti. La valutazione clinica è stata effettuata all’inizio della convivenza e al follow-up di 1, 3, 6 e 12 mesi. Strumenti utilizzati: BPRS, VGF, PWB, SQ, FAD. Analisi statistica: Modello Lineare Generale (GLM) con l’Analisi della Varianza per prove ripetute e calcolo dell’effect-size. Risultati. 15 pazienti maschi e 5 femmine, 17 italiani. 11 soddisfano i criteri diagnostici (DSM-IV-TR) per schizofrenia e disturbi psicotici, 5 per i disturbi dell’umore e 4 per i disturbi di personalità. Dopo l’inserimento 3 sono stati i ricoveri e 4 le visite psichiatriche urgenti. 8 pazienti modificano/diminuiscono la terapia e 3 la sospendono. Aumenta il benessere psicologico (PWB); diminuiscono i sintomi psicopatologici (BPRS ed SQ) e migliora il funzionamento globale (VFG). Il gruppo dei famigliari composto da 11 uomini e 9 donne, 19 di nazionalità italiana; con età media di 55 anni. 8 sono coniugati, 6 celibi/nubili, 4 divorziati e 2 vedovi. 9 hanno figli, 11 lavorano e 8 sono pensionati. Nei famigliari aumenta il benessere psicologico (PWB), migliora il funzionamento famigliare (FAD) e la valutazione del funzionamento globale (VGF) rimane costante nel tempo. Discussioni e conclusioni. Il progetto IESA sembra migliorare la psicopatologia, con una diminuzione dei comportamenti maladattativi e un aumento delle capacità relazionali dell’ospite favorendone l’integrazione. Inoltre, lo IESA sembra diminuire i costi della cronicità psichiatrica: diminuzione degli accessi al Pronto Soccorso, delle visite psichiatriche urgenti e delle giornate di ricovero.

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This work aims at exploring the relationship between business cycles, having frequencies rooted in the short run, and climatic phenomena, which span longer time horizons. The ultimate goal is to provide a theoretical framework to address these questions: How could very long run considerations affect short run economic decisions? How short run and transitory decisions could exert a long lasting effect on climate? This is achieved by means of an off-the-shelf real business cycle (RBC) model augmented so as to include a climatic block. The economy is perturbed by a technology shock and an energy-price shock. In general, the model performs relatively well in reproducing the cyclical characteristics of the economic variables; however, it is not as successful in capturing the cyclical behavior of climatic variables. Finally, it proposes a set of policy experiments, all taking the form of an energy tax directly or indirectly linked to the climatic status. As a matter of fact the effect of any tax responsive to the business cycle shows positive aspects: when a technology shock hits the economy, it mitigates global warming with minor costs in terms of potential output losses. It also protects the economy from an increase in energy prices, sustaining a certain level of output despite the fall in fossil energy use.

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The interpretation of phase equilibrium and mass transport phenomena in gas/solvent - polymer system at molten or glassy state is relevant in many industrial applications. Among tools available for the prediction of thermodynamics properties in these systems, at molten/rubbery state, is the group contribution lattice-fluid equation of state (GCLF-EoS), developed by Lee and Danner and ultimately based on Panayiotou and Vera LF theory. On the other side, a thermodynamic approach namely non-equilibrium lattice-fluid (NELF) was proposed by Doghieri and Sarti to consistently extend the description of thermodynamic properties of solute polymer systems obtained through a suitable equilibrium model to the case of non-equilibrium conditions below the glass transition temperature. The first objective of this work is to investigate the phase behaviour in solvent/polymer at glassy state by using NELF model and to develop a predictive tool for gas or vapor solubility that could be applied in several different applications: membrane gas separation, barrier materials for food packaging, polymer-based gas sensors and drug delivery devices. Within the efforts to develop a predictive tool of this kind, a revision of the group contribution method developed by High and Danner for the application of LF model by Panayiotou and Vera is considered, with reference to possible alternatives for the mixing rule for characteristic interaction energy between segments. The work also devotes efforts to the analysis of gas permeability in polymer composite materials as formed by a polymer matrix in which domains are dispersed of a second phase and attention is focused on relation for deviation from Maxwell law as function of arrangement, shape of dispersed domains and loading.

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The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.